Here's a guide on how I got Clerk.dev authentication working on my Chrome Extension. It's a wild experiment! ⚗️
- Authentication should work in Chrome Extension
- The authentication flow should be seamless
| import openai # pip install openai | |
| import typer # pip install "typer[all]" | |
| from rich import print # pip install rich | |
| from rich.table import Table | |
| """ | |
| Webs de interés: | |
| - Módulo OpenAI: https://github.com/openai/openai-python | |
| - Documentación API ChatGPT: https://platform.openai.com/docs/api-reference/chat | |
| - Typer: https://typer.tiangolo.com |
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
| #!/usr/bin/env bash | |
| # This script launches a Windows executable using Proton within a Linux environment. | |
| # It requires exactly one argument: the path to the executable to run. | |
| # It sets up a separate Proton prefix for each executable to avoid conflicts. | |
| # Usage: proton <path-to-executable> | |
| if [ "$#" -ne 1 ]; then | |
| echo "Usage: $0 <executable-path>" | |
| exit 1 |
| #!/bin/bash | |
| organizar() { | |
| local file="$1" | |
| # ignora se não for arquivo regular | |
| [ -f "$file" ] || return | |
| ext="${file##*.}" |
Ubiquiti markets the Enterprise Fortress Gateway (EFG) as a 25-gigabit-class router. The product page lists two 25 GbE SFP28 ports for WAN/LAN, and Ubiquiti positions the device as a flagship for medium and large enterprise deployments. Its silicon — a Marvell Octeon CN9670 — supports hardware-accelerated forwarding through purpose-built network engines (NIX) that should sustain tens of millions of packets per second. The UDM Beast, Ubiquiti's next-generation gateway, pairs a Marvell Octeon CN10K SoC (with ARM Neoverse N2 cores) with a dedicated Marvell Prestera-class switching ASIC accessed via PCIe — capabilities that, properly used, would offload most of the per-packet forwarding work into hardware.
| Symbol | ALT Code | ALT X Code | Symbol Name | HTML Entity DEC | HTML Entity HEX | HTML Entity Named | Unicode Code Point |
|---|---|---|---|---|---|---|---|
| ☐ | ALT 9744 | 2610 ALT X | Ballot box, check box, tick box | ☐ | ☐ | U+2610 | |
| ☑ | ALT 9745 | 2611 ALT X | Ballot box with check | ☑ | ☑ | U+2611 | |
| ☒ | ALT 9746 | 2612 ALT X | Ballot box with X | ☒ | ☒ | U+2612 | |
| ✅ | ALT 9989 | 2705 ALT X | White heavy check mark | ✅ | ✅ | U+2705 | |
| ✓ | ALT 10003 | 2713 ALT X | Check mark | ✓ | ✓ | ✓ | U+2713 |
| ✔ | ALT 10004 | 2714 ALT X | Heavy check mark | ✔ | ✔ | U+2714 |